352 citations · 1k across the 42 of their papers we have counts for
8 papers · 1 filter
Balancing Safety and Helpfulness in Healthcare AI Assistants through Iterative Preference Alignment
Huy Nghiem, Swetasudha Panda, Devashish Khatwani +3
Large Language Models (LLMs) are increasingly used in healthcare, yet ensuring their safety and trustworthiness remains a barrier to deployment. Conversational medical assistants m…
OG-Rank: Learning to Rank Fast and Slow with Uncertainty and Reward-Trend Guided Adaptive Exploration
Praphul Singh, Corey Barrett, Sumana Srivasta +3
Clinicians need ranking systems that work in real time and still justify their choices. Motivated by the need for a low-latency, decoder-based reranker, we present OG-Rank, a singl…
JEDA: Query-Free Clinical Order Search from Ambient Dialogues
Praphul Singh, Corey Barrett, Sumana Srivasta +4
Clinical conversations mix explicit directives (order a chest X-ray) with implicit reasoning (the cough worsened overnight, we should check for pneumonia). Many systems rely on LLM…
Optimizing Long-Form Clinical Text Generation with Claim-Based Rewards
Samyak Jhaveri, Praphul Singh, Jangwon Kim +2
Automating clinical documentation with large language models requires precise alignment with priorities such as completeness and factual grounding. We present an evaluation-integra…
RadAgents: Multimodal Agentic Reasoning for Chest X-ray Interpretation with Radiologist-like Workflows
Kai Zhang, Corey D Barrett, Jangwon Kim +3
Agentic systems offer a potential path to solve complex clinical tasks through collaboration among specialized agents, augmented by tool use and external knowledge bases. Neverthel…
Permissioned LLMs: Enforcing Access Control in Large Language Models
Bargav Jayaraman, Virendra J. Marathe, Hamid Mozaffari +2
In enterprise settings, organizational data is segregated, siloed and carefully protected by elaborate access control frameworks. These access control structures can completely bre…
RedactOR: An LLM-Powered Framework for Automatic Clinical Data De-Identification
Praphul Singh, Charlotte Dzialo, Jangwon Kim +4
Ensuring clinical data privacy while preserving utility is critical for AI-driven healthcare and data analytics. Existing de-identification (De-ID) methods, including rule-based te…
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey
Bo Ni, Zheyuan Liu, Leyao Wang +17
Retrieval-Augmented Generation (RAG) is an advanced technique designed to address the challenges of Artificial Intelligence-Generated Content (AIGC). By integrating context retriev…